Metabolomics-Based Machine Learning Models Accurately Predict Breast Cancer Estrogen Receptor Status.

Breast cancer is a global concern as a leading cause of death for women. Early and precise diagnosis can be vital in handling the disease efficiently. Breast cancer subtyping based on estrogen receptor (ER) status is crucial for determining prognosis and treatment.

Identification of a Novel Biomarker Panel for Breast Cancer Screening.

Breast cancer remains a major public health concern, and early detection is crucial for improving survival rates. Metabolomics offers the potential to develop non-invasive screening and diagnostic tools based on metabolic biomarkers. However, the inherent complexity of metabolomic datasets and the high dimensionality of biomarkers complicates the identification of diagnostically relevant features, with multiple studies demonstrating limited consensus on the specific metabolites involved.

Use of amantadine in the evaluation of response to chemotherapy in lung cancer: a pilot study.

Aim: The assessment of tumor response to therapy is of critical importance as it permits for a prospective end point evaluation and provides a guide to clinicians for making future treatment decisions. However, current practices in early evaluation of chemotherapy are insufficient. Amantadine is a substrate for .